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IBM Research - IrelandIBM Research - Ireland
© 2012 IBM Corporation
Future Life and ServicesShake up your City
Pól Mac Aonghusa,IBM Research – Ireland
IBM Research - IrelandIBM Research - Ireland
© 2012 IBM Corporation
By the middle of this Century, most of humanity will live in Cities that are increasingly instrumented & interconnected. In 2013 we expect to generate >850 Exabytes of Internet data. Most of it will be user contributed content (versus traditional enterprise sources).
Global access to technology is already driving trends like ‘virtual citizenship’, ‘virtual employment’ & ‘social innovation’
City + Citizen contributed content will become a core strategic economic resource – and the most scalable natural resource a City possesses.
Mobility, Openness & connection
will matter more than presence & rigid structures
Imagining Future Life: Interactions and Expectations
On-demand interaction will increasingly be the norm for a global community of virtual citizen innovators … who expect their experience of a City to be as simple as using an appliance
IBM Research - IrelandIBM Research - Ireland
© 2012 IBM Corporation
Imagining Future Services: Interdependency and Complexity
We have built a world of massive complexity and interdependency….
….and along with progress, we have brought on massive risks we don’t manage well
24 Hours of Air Travel Global Trade Global Financial Markets
Nuclear Technology
Pandemics Global Financial Crisis Nuclear Disasters
IBM Research - IrelandIBM Research - Ireland
© 2012 IBM Corporation
Some Good News: The future is already here -- it’s just not very evenly distributed*
• Linz, Austria• Solar City, an entire district exclusively using solar power for energy.
• Milan, Italy, Southampton, UK, Salzburg, Austria• Unified smart card access across services, i.e., bus, library, museum, bikes, and EV rental.
• Stockholm, Sweden• Congestion charging and real-time information from taxi and lorry GPS, traffic and pollution sensors, transit
systems, and weather • 20% reduction in city traffic, and halving the average travel time• 40% reduction in GHG, such as CO2
• Barcelona• EV innovation: >250 charge points, all with real-time status, free city parking and charging, 3% of parking spaces
reserved for EVs.
• Madrid• Fully integrated its emergency management systems (fire, police, ambulance) with responsiveness increased by
25% (>8 minutes)
• Amsterdam• Public/private platform to collaborate on aggressive goals:
• Municipal organizations climate-impact neutral before 2015• 20% renewable energy by 2025, • 40% reduction in CO2 emissions by 2025
*William Gibson
IBM Research - IrelandIBM Research - Ireland
© 2012 IBM Corporation
Three urgent challenges on the Future Cities roadmap
• Assimilate Data at Internet Scale– Diversity, heterogeneity
– Accuracy, sparsity, resilience
– Volume, provenance, privacy
• Model Human Demand– Understand how people use the
city infrastructure– Infer demand patterns
• Factor in Uncertainty– Operations and planning– Organise and open data and
knowledge, to engage citizens, empower universities and enable business
IBM Research - IrelandIBM Research - Ireland
© 2012 IBM Corporation
ReasonableCity: Learning Systems to Help Diagnose the City
ProblemHow can we provide City decision makers predict and diagnose events and anomalies in real-time from massive, rich, complex, heterogeneous and dynamic urban data?
Research Challenges• Identifying relevant data and information• Capturing and representing time-evolving
knowledge• Combining and correlating time-evolving
knowledge from heterogeneous data sources
• Advanced fusion of data
ApproachA system that identifies the nature and cause of changes and explain logical connection of knowledge across space and time
• Identify a common (semantic) representation layer for causality detection and analysis
• Develop a reasoning engine that interprets causality for diagnosis
• Demonstrate the prototype with DCC Data
• Improve the flexibility of causality detection (through ML techniques)
IBM Research - IrelandIBM Research - Ireland
© 2012 IBM CorporationDiagnosing Cities: A Road Traffic Congestion CaseFreddy Lecue, Anika Schumann, Marco Sbodio
Example … simplify decision making with smart systems that learn
IBM Research - IrelandIBM Research - Ireland
© 2012 IBM Corporation
Pervasive Technologies Datasets as Digital Footprints
Understand how people use the city's infrastructure
Mobility (transportation mode)
Consumption (energy, water, waste)
Environmental impact (noise, pollution)
Applications
Improve city’s services Optimize planning
Minimizing operational costs
Create feedback loops with citizens to reduce energy consumption and environmental impact
IBM Research - IrelandIBM Research - Ireland
© 2012 IBM Corporation
• Objectives
• What is the relationship between the on-line and physical communities … and what does it mean?
• Can we use this data to help adapt or anticipate service demand?
• Can we characterise city spaces for service operation and planning?
Example … interpreting human behavior to model demand
ApplicationsHelp region and city to better plan or adjust operations
Adjust service catchment areas (e.g. hospital serviced neighbors)
Plan new transit systems to help connecting areas with low interaction
IBM Research - IrelandIBM Research - Ireland
© 2012 IBM Corporation
…and uncertainty is everywhere!
River basins, coastal bays and estuaries
Households
Water treatment and distribution networks
Water shortagesIncreased costs
Water quality issues
Water shortagesIncreased costs
Water quality issues
Stress on water qualityFloods
Stress on water qualityFloods
Capacity shortagesIncreased investment and operating costs
Capacity shortagesIncreased investment and operating costs
Population growth
Climate change
Renewable energy
Water consumption
Rainfall patternsModel accuracy Measurements
Economicclimate
All these systems are connected in some
way – their IT solutions should be
too!Equipment failure
And…solutions should address uncertainty for robust design, planning, and information sharing
IBM Research - IrelandIBM Research - Ireland
© 2012 IBM Corporation
Valve PlacementValve Placement
Active and Robust Water Distribution Network Management
• Robust pressure management with uncertain demand profiles– Optimization model* includes network hydraulics, and scales to very large urban
networks– Places valves and recommends outlet pressures to reduce leakage while satisfying
customer requirements
• Case study: Chapelizod District Metered Area (DMA) in Dublin– Up to 44% reduction in average pressure– Estimated 66 (16%) additional households can be served
Optimal valve placement Resulting pressure reduction
* Assistance from HRL on initial model
IBM Research - IrelandIBM Research - Ireland
© 2012 IBM Corporation
What could you do if you had access to all the public data of a city? Could you make the city run better, faster, cheaper? What new economic opportunities would emerge? (Dublin City Manager, 2011)
ChallengeHow can we make a ‘Future City’ as consumable and accessible as email?
Observation“After the telephone was introduced more than a century ago, Kurzweil says, it took 50 years for a quarter of the American population to get one. After the cell phone was introduced, it took only seven years.”
…. ‘Future Cities’ in < 7 years
Email was 40 years old in 2012!
IBM Research - IrelandIBM Research - Ireland
© 2012 IBM Corporation
Working harder is not sustainable
Cities require innovative approaches
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